Coupling different methods for overcoming the class imbalance problem L Nanni, C Fantozzi, N Lazzarini Neurocomputing 158, 48-61, 2015 | 140 | 2015 |
Prediction of human population responses to toxic compounds by a collaborative competition F Eduati, LM Mangravite, T Wang, H Tang, JC Bare, R Huang, T Norman, ... Nature biotechnology 33 (9), 933-940, 2015 | 120 | 2015 |
A machine learning approach for the identification of new biomarkers for knee osteoarthritis development in overweight and obese women N Lazzarini, J Runhaar, AC Bay-Jensen, CS Thudium, ... Osteoarthritis and cartilage 25 (12), 2014-2021, 2017 | 82 | 2017 |
RGIFE: a ranked guided iterative feature elimination heuristic for the identification of biomarkers N Lazzarini, J Bacardit BMC bioinformatics 18, 1-22, 2017 | 20 | 2017 |
Hard Data Analytics Problems Make for Better Data Analysis Algorithms: Bioinformatics as an Example J Bacardit, P Widera, N Lazzarini, N Krasnogor Big Data 2 (3), 164--176, 2014 | 15 | 2014 |
Functional networks inference from rule-based machine learning models N Lazzarini, P Widera, S Williamson, R Heer, N Krasnogor, J Bacardit BioData mining 9, 1-23, 2016 | 12 | 2016 |
A machine learning model on Real World Data for predicting progression to Acute Respiratory Distress Syndrome (ARDS) among COVID-19 patients N Lazzarini, A Filippoupolitis, P Manzione, H Eleftherohorinou PLoS One 17 (7), e0271227, 2022 | 9 | 2022 |
Identification of CNGB1 as a predictor of response to neoadjuvant chemotherapy in muscle-invasive bladder cancer AC Hepburn, N Lazzarini, R Veeratterapillay, L Wilson, J Bacardit, R Heer Cancers 13 (15), 3903, 2021 | 9 | 2021 |
Heterogeneous machine learning system for improving the diagnosis of primary aldosteronism N Lazzarini, L Nanni, C Fantozzi, A Pietracaprina, G Pucci, TM Seccia, ... Pattern Recognition Letters 65, 124-130, 2015 | 8 | 2015 |
Heterogeneous Ensembles for the Missing Feature Problem L Nanni, S Brahnam, C Fantozzi, N Lazzarini 2013 Annual Meeting of the Northeast Decision Sciences Institute,New York, 2013 | 6 | 2013 |
Characterising the influence of rule-based knowledge representations in biological knowledge extraction from transcriptomics data S Baron, N Lazzarini, J Bacardit Applications of Evolutionary Computation: 20th European Conference …, 2017 | 5 | 2017 |
Tecniche di apprendimento automatico per l'identificazione dell'iperaldosteronismo primario N Lazzarini | 1 | 2012 |
Knowledge extraction from biomedical data using machine learning N Lazzarini Newcastle University, 2017 | | 2017 |
Heterogeneous Machine Learning System for Diagnosing Primary Aldosteronism N Lazzarini, L Nanni, C Fantozzi, A Pietracaprina, G Pucci, MT Seccia, ... Journal of Hypertension 31 (e-Supplement A), e409, 2013 | | 2013 |